dc.contributor.advisor | Zeman, Daniel | |
dc.creator | Cayralat, Christian | |
dc.date.accessioned | 2022-04-06T11:06:29Z | |
dc.date.available | 2022-04-06T11:06:29Z | |
dc.date.issued | 2021 | |
dc.identifier.uri | http://hdl.handle.net/20.500.11956/147949 | |
dc.description.abstract | Orthography Standardization in Arabic Dialects Abstract Christian Cayralat1 1 Charles University Spontaneous orthography in Arabic dialects poses one of the biggest ob- stacles in the way of Dialectal Arabic NLP applications. As the Arab world enjoys a wide array of these widely spoken and recently written, non-standard, low-resource varieties, this thesis presents a detailed account of this relatively overlooked phenomenon. It sets out to show that continuously creating addi- tional noise-free, manually standardized corpora of Dialectal Arabic does not free us from the shackles of non-standard (spontaneous) orthography. Because real-world data will most often come in a noisy format, it also investigates ways to ease the amount of noise in textual data. As a proof of concept, we restrict ourselves to one of the dialectal varieties, namely, Lebanese Arabic. It also strives to gain a better understanding of the nature of the noise and its distri- bution. All of this is done by leveraging various spelling correction and morpho- logical tagging neural architectures in a multi-task setting, and by annotating a Lebanese Arabic corpus for spontaneous orthography standardization, and morphological segmentation and tagging, among other features. Additionally, a detailed taxonomy of spelling inconsistencies for... | en_US |
dc.language | English | cs_CZ |
dc.language.iso | en_US | |
dc.publisher | Univerzita Karlova, Matematicko-fyzikální fakulta | cs_CZ |
dc.subject | spell checking|automatic corrections|Arabic|dialect | en_US |
dc.subject | kontrola pravopisu|automatické opravy|arabština|dialekt | cs_CZ |
dc.title | Orthography Standardization in Arabic Dialects | en_US |
dc.type | diplomová práce | cs_CZ |
dcterms.created | 2021 | |
dcterms.dateAccepted | 2021-09-08 | |
dc.description.department | Institute of Formal and Applied Linguistics | en_US |
dc.description.department | Ústav formální a aplikované lingvistiky | cs_CZ |
dc.description.faculty | Matematicko-fyzikální fakulta | cs_CZ |
dc.description.faculty | Faculty of Mathematics and Physics | en_US |
dc.identifier.repId | 235817 | |
dc.title.translated | Normalizace pravopisu v arabských dialektech | cs_CZ |
dc.contributor.referee | Straňák, Pavel | |
thesis.degree.name | Mgr. | |
thesis.degree.level | navazující magisterské | cs_CZ |
thesis.degree.discipline | Matematická lingvistika | cs_CZ |
thesis.degree.discipline | Computational Linguistics | en_US |
thesis.degree.program | Computer Science | en_US |
thesis.degree.program | Informatika | cs_CZ |
uk.thesis.type | diplomová práce | cs_CZ |
uk.taxonomy.organization-cs | Matematicko-fyzikální fakulta::Ústav formální a aplikované lingvistiky | cs_CZ |
uk.taxonomy.organization-en | Faculty of Mathematics and Physics::Institute of Formal and Applied Linguistics | en_US |
uk.faculty-name.cs | Matematicko-fyzikální fakulta | cs_CZ |
uk.faculty-name.en | Faculty of Mathematics and Physics | en_US |
uk.faculty-abbr.cs | MFF | cs_CZ |
uk.degree-discipline.cs | Matematická lingvistika | cs_CZ |
uk.degree-discipline.en | Computational Linguistics | en_US |
uk.degree-program.cs | Informatika | cs_CZ |
uk.degree-program.en | Computer Science | en_US |
thesis.grade.cs | Výborně | cs_CZ |
thesis.grade.en | Excellent | en_US |
uk.abstract.en | Orthography Standardization in Arabic Dialects Abstract Christian Cayralat1 1 Charles University Spontaneous orthography in Arabic dialects poses one of the biggest ob- stacles in the way of Dialectal Arabic NLP applications. As the Arab world enjoys a wide array of these widely spoken and recently written, non-standard, low-resource varieties, this thesis presents a detailed account of this relatively overlooked phenomenon. It sets out to show that continuously creating addi- tional noise-free, manually standardized corpora of Dialectal Arabic does not free us from the shackles of non-standard (spontaneous) orthography. Because real-world data will most often come in a noisy format, it also investigates ways to ease the amount of noise in textual data. As a proof of concept, we restrict ourselves to one of the dialectal varieties, namely, Lebanese Arabic. It also strives to gain a better understanding of the nature of the noise and its distri- bution. All of this is done by leveraging various spelling correction and morpho- logical tagging neural architectures in a multi-task setting, and by annotating a Lebanese Arabic corpus for spontaneous orthography standardization, and morphological segmentation and tagging, among other features. Additionally, a detailed taxonomy of spelling inconsistencies for... | en_US |
uk.file-availability | V | |
uk.grantor | Univerzita Karlova, Matematicko-fyzikální fakulta, Ústav formální a aplikované lingvistiky | cs_CZ |
thesis.grade.code | 1 | |
uk.publication-place | Praha | cs_CZ |
uk.thesis.defenceStatus | O | |